Computational and data Grids in large-scale science and engineering
Future Generation Computer Systems - Grid computing: Towards a new computing infrastructure
On the Effect of Large-Scale Deployment of Parallel Downloading
WIAPP '03 Proceedings of the The Third IEEE Workshop on Internet Applications
Enabling the Co-Allocation of Grid Data Transfers
GRID '03 Proceedings of the 4th International Workshop on Grid Computing
Ten fallacies and pitfalls on end-to-end available bandwidth estimation
Proceedings of the 4th ACM SIGCOMM conference on Internet measurement
A speed-based adaptive dynamic parallel downloading technique
ACM SIGOPS Operating Systems Review
TCP-PARIS: a Parallel Download Protocol for Replicas
WCW '05 Proceedings of the 10th International Workshop on Web Content Caching and Distribution
Efficient Multi-Source Data Transfer in Data Grids
CCGRID '06 Proceedings of the Sixth IEEE International Symposium on Cluster Computing and the Grid
Redundant parallel data transfer schemes for the grid environment
ACSW Frontiers '06 Proceedings of the 2006 Australasian workshops on Grid computing and e-research - Volume 54
Grid Resource Monitoring and Selection for Rapid Turnaround Applications
IEICE - Transactions on Information and Systems
Efficient reuse of replicated parallel data segments in computational grids
Future Generation Computer Systems
Future Generation Computer Systems
Mcitp self-paced training kit (exam 70-443): designing a database server infrastructure using microsoft® sql server™ 2005
Replica selection on co-allocation data grids
ISPA'04 Proceedings of the Second international conference on Parallel and Distributed Processing and Applications
Improving job scheduling performance with parallel access to replicas in Data Grid environment
The Journal of Supercomputing
Replication techniques in data grid environments
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part II
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In data grid environments, data replication services increase the reliability and the availability of the data sets. Using replicas, a data set can be downloaded from many servers simultaneously in order to improve the performance of the data transfer. However, the servers selected may become slow or congested. Therefore, it should be replaced dynamically. In this paper, we propose a method to improve the efficiency of downloading by reevaluating the conditions of all servers that can supply the dataset during the download progress. Current servers used for downloading, if perform unsatisfactorily, will be replaced by others that meet the performance criteria. In all previous schemes in parallel downloading, the load of an ill performing server will be just transferred to a more powerful server. However, intuitively if there are idle servers around that also have this data, why not use them? Therefore, our method will monitor all servers that can supply the data even if a server is not involved in the download process initially. Loads may be transferred from a working server to a non-working server, not just transferred to another working server. Furthermore, to decide the suitability of a server, we consider not only the connection bandwidth but also the status within a server such as CPU and memory usage. We implement our method in a real grid environment. Our method decreases the completion time by 1.63%-13.45% in the real grid environment and by 6.28%-30.56% in the grid environment with other injected load when compared to the recursive co-allocation scheme. It shows that the proposed scheme adapts to the dynamic environment nicely and decreases the total download time effectively.